Jessilyn Dunn

Total Synthesis of a Functional Designer Eukaryotic Chromosome

Designer Chromosome One of the ultimate aims of synthetic biology is to build designer organisms from the ground up. Rapid advances in DNA synthesis has allowed the assembly of complete bacterial genomes. Eukaryotic organisms, with their generally much larger and more complex genomes, present an additional challenge to synthetic biologists. Annaluru et al. (p. 55, published online 27 March) designed a synthetic eukaryotic chromosome based on yeast chromosome III. The designer chromosome, shorn of destabilizing transfer RNA genes and transposons, is ∼14% smaller than its wild-type template and is fully functional with every gene tagged for easy removal. A synthetic version of yeast chromosome III with every gene tagged can substitute for the original. Rapid advances in DNA synthesis techniques have made it possible to engineer viruses, biochemical pathways and assemble bacterial genomes. Here, we report the synthesis of a functional 272,871–base pair designer eukaryotic chromosome, synIII, which is based on the 316,617–base pair native Saccharomyces cerevisiae chromosome III. Changes to synIII include TAG/TAA stop-codon replacements, deletion of subtelomeric regions, introns, transfer RNAs, transposons, and silent mating loci as well as insertion of loxPsym sites to enable genome scrambling. SynIII is functional in S. cerevisiae. Scrambling of the chromosome in a heterozygous diploid reveals a large increase in a-mater derivatives resulting from loss of the MATα allele on synIII. The complete design and synthesis of synIII establishes S. cerevisiae as the basis for designer eukaryotic genome biology.

Decreased S-Nitrosylation of Tissue Transglutaminase Contributes to Age-Related Increases in Vascular Stiffness

Rationale: Although an age-related decrease in NO bioavailability contributes to vascular stiffness, the underlying molecular mechanisms remain incompletely understood. We hypothesize that NO constrains the activity of the matrix crosslinking enzyme tissue transglutaminase (TG2) via S-nitrosylation in young vessels, a process that is reversed in aging. Objective: We sought to determine whether endothelium-dependent NO regulates TG2 activity by S-nitrosylation and whether this contributes to age-related vascular stiffness. Methods and Results: We first demonstrate that NO suppresses activity and increases S-nitrosylation of TG2 in cellular models. Next, we show that nitric oxide synthase (NOS) inhibition leads to increased surface and extracellular matrix–associated TG2. We then demonstrate that endothelium-derived bioactive NO primarily mediates its effects through TG2, using TG2−/− mice chronically treated with the NOS inhibitor l-NG-nitroarginine methyl ester (L-NAME). We confirm that TG2 activity is modulated by endothelium-derived bioactive NO in young rat aorta. In aging rat aorta, although TG2 expression remains unaltered, its activity increases and S-nitrosylation decreases. Furthermore, TG2 inhibition decreases vascular stiffness in aging rats. Finally, TG2 activity and matrix crosslinks are augmented with age in human aorta, whereas abundance remains unchanged. Conclusions: Decreased S-nitrosylation of TG2 and increased TG activity lead to enhanced matrix crosslinking and contribute to vascular stiffening in aging. TG2 appears to be the member of the transglutaminase family primarily contributing to this phenotype. Inhibition of TG2 could thus represent a therapeutic target for age-associated vascular stiffness and isolated systolic hypertension.

Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information

A new wave of portable biosensors allows frequent measurement of health-related physiology. We investigated the use of these devices to monitor human physiological changes during various activities and their role in managing health and diagnosing and analyzing disease. By recording over 250,000 daily measurements for up to 43 individuals, we found personalized circadian differences in physiological parameters, replicating previous physiological findings. Interestingly, we found striking changes in particular environments, such as airline flights (decreased peripheral capillary oxygen saturation [SpO2] and increased radiation exposure). These events are associated with physiological macro-phenotypes such as fatigue, providing a strong association between reduced pressure/oxygen and fatigue on high-altitude flights. Importantly, we combined biosensor information with frequent medical measurements and made two important observations: First, wearable devices were useful in identification of early signs of Lyme disease and inflammatory responses; we used this information to develop a personalized, activity-based normalization framework to identify abnormal physiological signals from longitudinal data for facile disease detection. Second, wearables distinguish physiological differences between insulin-sensitive and -resistant individuals. Overall, these results indicate that portable biosensors provide useful information for monitoring personal activities and physiology and are likely to play an important role in managing health and enabling affordable health care access to groups traditionally limited by socioeconomic class or remote geography.

Flow-Dependent Epigenetic DNA Methylation in Endothelial Gene Expression and Atherosclerosis

Epigenetic mechanisms that regulate endothelial cell gene expression are now emerging. DNA methylation is the most stable epigenetic mark that confers persisting changes in gene expression. Not only is DNA methylation important in rendering cell identity by regulating cell type-specific gene expression throughout differentiation, but it is becoming clear that DNA methylation also plays a key role in maintaining endothelial cell homeostasis and in vascular disease development. Disturbed blood flow causes atherosclerosis, whereas stable flow protects against it by differentially regulating gene expression in endothelial cells. Recently, we and others have shown that flow-dependent gene expression and atherosclerosis development are regulated by mechanisms dependent on DNA methyltransferases (1 and 3A). Disturbed blood flow upregulates DNA methyltransferase expression both in vitro and in vivo, which leads to genome-wide DNA methylation alterations and global gene expression changes in a DNA methyltransferase-dependent manner. These studies revealed several mechanosensitive genes, such as HoxA5, Klf3, and Klf4, whose promoters were hypermethylated by disturbed blood flow, but rescued by DNA methyltransferases inhibitors such as 5Aza-2-deoxycytidine. These findings provide new insight into the mechanism by which flow controls epigenomic DNA methylation patterns, which in turn alters endothelial gene expression, regulates vascular biology, and modulates atherosclerosis development.

S-Nitrosation of arginase 1 requires direct interaction with inducible nitric oxide synthase

Arginase constrains endothelial nitric oxide synthase activity by competing for the common substrate, l-Arginine. We have recently shown that inducible nitric oxide synthase (NOS2) S-nitrosates and activates arginase 1 (Arg1) leading to age-associated vascular dysfunction. Here, we demonstrate that a direct interaction of Arg1 with NOS2 is necessary for its S-nitrosation. The specific domain of NOS2 that mediates this interaction is identified. Disruption of this interaction in human aortic endothelial cells prevents Arg1 S-nitrosation and activation. Thus, disruption of NOS2–Arg1 interaction may represent a therapeutic strategy to attenuate age related vascular endothelial dysfunction.

Personal Omics for Precision Health

The convergence of scientific capability and technology that generates vast health data at diminishing cost has generated opportunities, challenges, and anticipation surrounding future data-centric healthcare models. Individualized health data spanning biomolecular, physiological, and environmental dimensions comprise a personal omics profile. Here, we discuss methods and opportunities to bridge genome and dynamic physiology, detect disease at an early stage, and uncover lifestyle and environmental patterns associated with the disease. Significant challenges exist to aggregate, integrate, and protect personal omics data to advance our understanding of the disease, enable data-driven clinical decisions, and motivate individuals to sustain behavioral change. Since the first sequencing of the human genome in 2003, the relationship between genetic variants and phenotypes has remained a central challenge in medicine. Many diseases including coronary atherosclerosis are polygenic or indeed omnigenic wherein many variants work together to impact a phenotype.1 Potentially confounding factors and small study population size in comparison to the size of the human genome make it challenging to decipher genetic risk for complex and heterogeneous diseases. To better understand how genetic variation maps to complex traits, simultaneous measurements that bridge genotype and phenotype are required. This deep phenotyping is the goal of personal omics profiling,2 which combines measures of the genome, epigenome, transcriptome, proteome, metabolome, and additional omes (Figure [A]). Rapid advances in sequencing and mass spectrometry drive continued improvement in cost, accuracy, and throughput.3,4 Mobile and wearable technologies enable physiological, contextual, and environmental measurements. As we learn more about the symbiotic functions of the microbiome in human health, we also apply multiomic profiling to microbial populations (Figure [B]). Together these measurements provide a holistic profile of dynamic health and facilitate personalized, precision interventions based on predictive models (Figure [E]). Figure. Overview of personal omics. A , Omic measures span …

High Frequency Actionable Pathogenic Exome Mutations in an Average-Risk Cohort

Whole exome sequencing (WES) is increasingly utilized in both clinical and non-clinical settings, but little is known about the utility of WES in healthy individuals. In order to determine the frequency of both medically actionable and non-actionable but medically relevant exome findings in the general population we assessed the exomes of 70 participants who have been extensively characterized over the past several years as part of a longitudinal integrated multi-omics profiling study at Stanford University. We assessed exomes for rare likely pathogenic and pathogenic variants in genes associated with Mendelian disease in the Online Mendelian Inheritance in Man (OMIM) database. We used American College of Medical Genetics (ACMG) guidelines were used for the classification of rare sequence variants, and additionally we assessed pharmacogenetic variants. Twelve out of 70 (17%) participants had medically actionable findings in Mendelian disease genes, including 6 (9%) with mutations in genes not currently included in the ACMG’s list of 59 actionable genes. This number is higher than that reported in previous studies and suggests added benefit from utilizing expanded gene lists and manual curation to assess actionable findings. A total of 60 participants (89%) had non-actionable findings identified including 57 who were found to be mutation carriers for recessive diseases and 21 who have increased Alzheimer’s disease risk due to heterozyg ous or homozygous APOE e4 alleles (18 participants had both). These results suggest that exome sequencing may have considerably more utility for health management in the general population than previously thought.

Wearables and the medical revolution

Wearable sensors are already impacting healthcare and medicine by enabling health monitoring outside of the clinic and prediction of health events. This paper reviews current and prospective wearable technologies and their progress toward clinical application. We describe technologies underlying common, commercially available wearable sensors and early-stage devices and outline research, when available, to support the use of these devices in healthcare. We cover applications in the following health areas: metabolic, cardiovascular and gastrointestinal monitoring; sleep, neurology, movement disorders and mental health; maternal, pre- and neo-natal care; and pulmonary health and environmental exposures. Finally, we discuss challenges associated with the adoption of wearable sensors in the current healthcare ecosystem and discuss areas for future research and development.